Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

12 papers of 11,817Sort Recent · Most cited
  1. 2026
  2. 2026
  3. 2026
    PADP: progressive and adaptive data pruning for efficient incremental learningBiqing Duan, Di Liu, Zhenli He … Shengfa MiaoScientific Reports
  4. 2026
  5. 2025
    Multi-Attribute Continual Learning for Blind Image Quality AssessmentYunhao Luo, Jin-Ming Liu, Wei Zhou, Xin JinInternational Symposium on Circuits and Systems
  6. 2025
    LODAP: On-Device Incremental Learning Via Lightweight Operations and Data PruningBiqing Duan, Qing Wang, Di Liu … Shengfa MiaoJournal of systems architecture
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  7. 2025
    CalFuse: Multi-Modal Continual Learning via Feature Calibration and Parameter FusionJun-Cen Guo, Siao Liu, Xiaoguang Zhu … Liang SongarXiv
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  8. 2023
    An adaptive incremental TSK fuzzy system based on stochastic configuration and its approximation capability analysisWei Zhou, De-Gang Wang, Hongxing Li, Menghong BaoJournal of Intelligent & Fuzzy Systems
  9. 2023
  10. 2021
    LIQA: Lifelong Blind Image Quality AssessmentJianzhao Liu, Wei Zhou, Xin Li … Zhibo ChenIEEE Trans. Multimedia · University of Science and Technology of China
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  11. 2022
    Intergroup Cascade Broad Learning System With Optimized Parameters for Chaotic Time Series PredictionJun Yi, Jiahua Huang, Wei Zhou … Meng ZhaoIEEE TAI · Chongqing University of Science and Technology
  12. 2021
    A Fixed Version of Quadratic Program in Gradient Episodic MemoryWei Zhou, Yiying LiarXiv · National University of Defense Technology
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About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.